Pricing Strategy Analyst

We are seeking a Pricing Strategy Analyst to help shape and implement pricing strategies that drive growth, improve conversion rates, and enhance profitability. You will analyze customer behavior, pricing performance, competitive trends, and market dynamics to generate insights that support decision-making across the business. This role is ideal for someone who is analytical, curious, and passionate about using data to influence strategy.

Key Responsibilities

• Analyze pricing data across manufacturing processes, materials, regions, and customer segments to identify trends and optimization opportunities.
• Build models and simulations to assess the impact of pricing changes on margin, conversion, customer acquisition, and supplier engagement.
• Support the development of Xometry’s proprietary AI pricing engine through rigorous data analysis, testing, and performance insights.
• Design and evaluate A/B tests to assess the effectiveness of pricing strategies and product enhancements.
• Collaborate with cross-functional teams including Product, Data Science, Sales, and Operations to develop integrated pricing approaches.
• Monitor key pricing KPIs and support the continuous improvement of dynamic pricing algorithms.
• Conduct competitive and market analysis to benchmark pricing and identify emerging trends.

Qualifications

• Bachelor’s degree in Economics, Mathematics, Statistics, Engineering, Finance, or a related field (advanced degree is a plus).
• 2+ years of experience in pricing, analytics, strategy, or similar roles—preferably in e-commerce, marketplaces, or B2B platforms.
• Proficiency in Excel and SQL; experience with BI tools (e.g., Looker, Tableau) and statistical programming languages (Python, R) is a plus.
• Strong analytical skills and the ability to communicate data-driven insights effectively.
• Comfortable working in a fast-paced, data-driven environment.
• Excellent collaboration, problem-solving, and communication skills.

Preferred Qualifications

• Experience with dynamic pricing, elasticity modeling, or AI-driven pricing tools.
• Familiarity with manufacturing processes or supply chain economics.
• Comfortable working with large and complex datasets, including collaboration with data engineering and data science teams to build data pipelines.